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相关概念视频

Range00:59

Range

11.2K
The range is one of the measures of variation. It can be defined as the difference between a dataset's highest and lowest values. For example, in the study of seven 16-ounce soda cans, the filled volume of soda was measured, thus producing the following amount (in ounces) of soda:
15.9; 16.1; 15.2; 14.8; 15.8; 15.9; 16.0; 15.5
Measurements of the amount of soda in a 16-ounce can vary since different subjects record these measurements or since the exact amount - 16 ounces of liquid, was not...
11.2K
Midrange01:07

Midrange

3.6K
A somewhat easy to compute quantitative estimate of a data set’s central tendency is its midrange, which is defined as the mean of the minimum and maximum values of an ordered data set.
Simply put, the midrange is half of the data set’s range. Similar to the mean, the midrange is sensitive to the extreme values and hence the prospective outliers. However, unlike the mean, the midrange is not sensitive to all the values of the data set that lie in the middle. Thus, it is prone to...
3.6K
Interpreting R Charts01:22

Interpreting R Charts

62
R chart, or range chart, is a fundamental tool in statistical process control used to monitor the variability within a process. It complements the X-bar (x̄) chart by focusing on the range of the data, rather than individual values, providing a clear picture of the process dispersion over time.
An R chart plots the range of subsets of measurements collected from a process. Each point on the chart represents the range—defined as the difference between the maximum and minimum...
62
Electronic Distance Measuring Instruments01:30

Electronic Distance Measuring Instruments

31
Electronic Distance Measuring Instruments (EDMs) are essential tools in modern surveying, offering precise distance measurements by emitting electromagnetic signals and calculating the time required for these signals to travel to a target and return. Two primary types of signals are used in EDMs — light waves and microwaves — each suited to specific environmental and distance requirements. Light-wave-based EDMs utilize either infrared or laser light, providing high accuracy over short...
31
The R Chart01:02

The R Chart

76
In statistical process control, control charts, particularly R charts, are instrumental in monitoring process variations and identifying non-random patterns that run charts might miss. R charts track the variability within process subgroups, which is crucial when standard deviation use is impractical or unknown process variations exist.
R charts are pivotal for pinpointing shifts in process variability. Stability is indicated when all data points remain within the defined upper and lower...
76
Response Surface Methodology01:16

Response Surface Methodology

107
Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
107

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相关实验视频

Updated: Jun 18, 2025

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street
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Published on: January 20, 2023

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通过修改范围调整的措施评估物流行业的效率.

Chongyu Ma1, Jianwei Ren2, Chunhua Chen3

  • 1Transportation Institute, Inner Mongolia University, Hohhot, 010000, China.

Scientific reports
|July 31, 2024
PubMed
概括

一个新的修改范围调整措施 (MRAM) 模型改善了物流效率评估. 与现有模型相比,这种增强方法提供了更准确的结果,有助于识别和优化生产问题.

关键词:
数据包裹分析数据包裹分析.物流行业的效率效率物流行业的效率效率.修改的界限 修改的界限测量范围调整措施范围调整措施

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相关实验视频

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科学领域:

  • 运营研究 运营研究
  • 物流管理物流管理
  • 数据包围分析 数据包围分析

背景情况:

  • 准确评估物流效率对于识别生产问题和优化运营至关重要.
  • 现有的范围调整措施 (RAM) 模型仅限于根据规模条件的可变回报.
  • 需要一种更通用的效率评估方法,适用于不同的规模条件.

研究的目的:

  • 开发一个修改范围调整措施 (MRAM) 模型,以提高物流效率评估.
  • 调整RAM模型以适应常量回报 (CRS) 条件.
  • 用现实物流数据验证MRAM模型的实用性和准确性.

主要方法:

  • 在恒定回归规模下开发RAM-CRS模型.
  • 引入辐射模型来定义MRAM的输入下限和输出上限.
  • 应用和比较MRAM模型与RAM-CRS以及使用18个省份物流数据的添加模型.

主要成果:

  • 由于过度限制范围的限制,RAM-CRS模型的效率值被发现相对较低.
  • 随着其修改的边界,MRAM模型有效地减轻了RAM-CRS模型的限制.
  • 对比分析表明,MRAM模型提供了比添加模型更准确的效率测量.

结论:

  • MRAM 模型为物流效率评估提供了更灵活,更准确的方法,特别是在恒定的规模回报的情况下.
  • 与RAM-CRS相比,MRAM的修改后的边界允许更现实的效率评估.
  • 该MRAM模型是识别生产问题和支持物流优化工作的宝贵工具.